• Journal of the Korean Operations Research and Management Science Society
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• v.24 no.2
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• pp.69-80
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• 1999

A genetic algorithm to determine the optimal signal sequence and double cycle pattern is described. The signal sequence and double cycle pattern are used as the input for TRANSYT to find optimal signal timing at each junction in the area traffic networks, In the genetic process, the partially matched crossover and simple crossover operators are used for evolution of signal sequence and double cycle pattern respectively. A special conversion algorithm is devised to convert the signal sequence into the link-stage assignment for TRANSYT. Results from tests using data from an area traffic network in Leicester region R are given.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.32-35
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• 1996

Traffic signal cycle optimization is one of the most efficient ways for reducing fuel consumption and improving vehicle waiting time of highsaturated traffic conditions. But most research focused on lowsaturated traffic conditions. Only a few studies have researched traffic control for highsaturated traffic conditions. In this paper reviews the problem of conventional traffic signal system and creates optimal traffic cycle of at the bottom traffic intersection using 27 fuzzy rules. Moreover, to prevent spillback, it can adapt control even though upper traffic intersection has a different saturation rate, road length, road slope and road width.

• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.17-28
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• 2009

There are many limitations in dealing with rapidly changing traffic demand in urban cities. Thus recently, traffic operation and management skills are more emphasized rather than the expansion of traffic facilities. In particular, in the interrupted flow formed by signalized intersections, it is quite important to give optimal signal timing to each intersection with consideration of progression. However, as fixed signal times per direction can affect passing capacity in signalized intersections, the present four-signal phase including a left-turn signal has many limitations, including reduction of directional road capacity when traffic demand is increases dramatically during peak hours. Because of this problem, lots of studies about internal metering techniques for oversaturated signal control skills have progressed but these techniques are not used widely due to the absence of detectors for queue sensing in real-time signal control systems. In this research, a new methodology called the "restrictive left-turn signal control", which is already used at the intersection above Samsung subway station, is suggested in order to reduce control delay of urban arterial roads. The restrictive left-turn signal control allows a driver to make a U-turn and then a right turn instead of turning left in that intersection. With this change, the restrictive left-turn signal control can contribute to increased intersection capacity by reducing the number of signal phases and maximizing the through phase time. However, road structure and traffic conditions at the target intersections should be considered before the adoption of the proposed signal control.

• Journal of Korean Society of Transportation
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• v.29 no.2
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• pp.111-121
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• 2011

This paper discusses a method for optimizing the semi-actuated traffic signal control system by adjusting the initial interval according to the number of vehicles waiting for the green light in the actuated phase. We also present a Left-Turn actuated traffic signal control strategy that examines the vehicular noise in the detection area and determines the phase extension and the gap-out. In order to detect the vehicles in real-time, an image detector's Video Image Tracking technology was adopted. A 'Zone in Zone'method was implemented, and the image detection area is segmented into three zones: 1) Zone1 for verifying a vehicles obligatory presence, 2) Zone2 for counting the standby vehicles, and 3) Zone3 for examining the number of vehicles that have passed. The on-site assessment of the Left Turn Actuated Control is carried out using CORSIM, and the results show that the Control Delay decreased by 23.10%, 15.06%, and 4.34% compared to the delays resulted from pre-timed control, semi-actuated control-1 and semi-actuated control-2 traffic signal control systems respectively. The Queue Time also decreased by 36.24%, 20.10% and the Total Time by 14.36%, 7.02% for the same scenario. Which clearly demonstrates the operational efficiency. A sensitivity analysis reveals that the improvement from the propose traffic control strategy tends to increase as the through traffic volume reaches a saturated condition and the left-turn traffic volume decreases.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.421-428
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• 2007

This paper discusses a fitness of the control on intersection network using fuzzy analytic hierachy process. The validity of control of traffic signal on intersection is phase, cycle of intersection. But the aigent of traffic intersection network is relative of intersection article. Therefor the aigent of traffic network intersection is before intersection passing vechile number, delayed vechile number. Fuzzy analytic hierachy process clears the grade of validity of the fixed cycle time controller and adaptive fixed cycle time and fuzzy traffic controller and proposes a new control type a traffic signal by this fuzzy analytic hierachy process.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.143-148
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• 2024

Traffic congestion has caused issues in various forms such as the environment and economy. Recently, an intelligent transport system (ITS) using artificial intelligence (AI) has been focused so as to alleviate the traffic congestion problem. In this paper, we propose a reinforcement learning-based traffic signal control algorithm that can smooth the flow of traffic while reducing discomfort levels of drivers and pedestrians. By applying the proposed algorithm, it was confirmed that the discomfort levels of drivers and pedestrians can be significantly reduced compared to the existing fixed signal control system, and that the performance gap increases as the number of roads at the intersection increases.

• Proceedings of the Korea Contents Association Conference
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• 2004.11a
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• pp.501-504
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• 2004

Straight traffic signal information is understanded by roation traffic signal.Ten traffic rotation street flew system saturated without forseed quantaty of traffic vehicle and length oftraffic street.Optimul traffic signal forcasting is needed departmemtstore sale season. for solution of this problem, at least before 10 hour traffic quantity reported policy department.For traffic forcasting of traffic jamed building pushed vehicle, neural network method is adapted Single traffic network is more needed to through traffic signal compared of traffic network. traffic network system is first analysed for artificial traffic network system and networked traffic systen is constructed by ubiquatous.

• Journal of Korean Society of Transportation
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• v.26 no.6
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• pp.81-89
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• 2008

This paper aims to develop an integrated urban freeway exit-intersection actuated traffic signal control strategy based on which a real-time detection of queue at each of an exit-ramp and an arterial. To evaluate effects of the proposed actuated traffic signal control according to various traffic situations and geometric conditions, this paper analyzed the effects of the proposed traffic signal control strategy according to traffic situations such as the occasion of the arterial being saturated, the occasion of the exit-ramp being saturated, and the occasion of both the arterial and the exit-ramp being saturated. To reflect geometric conditions that influence the effects of the control strategy, this paper evaluated effects before and after applying the actuated traffic signal control strategy according to six cases for both above and under the downstream link length of 200m as proposed by COSMOS. The study results shown that when the link length above 200m, offered a greater effect of applying the actuated traffic control strategy than below 200m. Thus, the actuated traffic signal control through a real-time detection of queue is expected to offer a greater effect at longer downward link.

• Journal of Advanced Navigation Technology
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• v.21 no.5
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• pp.472-478
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• 2017

In this paper, we deals with optimizing traffic signal timing in grid networks by using a network topology design method. Optimizing traffic signal timing includes minimizing delay time delay between departure and destination by interlocking straight traffic signal in the minimum spanning tree(MST). On the assumption that users of network abide by the paths provided in this paper, this paper shows optimizing traffic signal timing in grid networks. the paths provided in this paper is gathered by using Dijkstra algorithm used in computer networks. The results indicate minimizing delay time of passing through the grid network and interlocking traffic signal in the grid network.

• Proceedings of the KOR-KST Conference
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• 2000.02a
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• pp.89-115
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• 2000

Traffic signal setting policies and traffic assignment procedures are mutually dependent. The combined signal control and traffic assignment problem deals with this interaction. With the total travel time minimization objective, gradient based local search methods are implemented. Deterministic user equilibrium is the selected user route choice rule, Webster's delay curve is the link performance function, and green time per cycle ratios are decision variables. Three implemented solution codes resulting in six variations include intersections operating under multiphase operation with overlapping traffic movements. For reference, the iterative approach is also coded and all codes are tested in four example networks at five demand levels. The results show the numerical gradient estimation procedure performs best although the simplified local searches show reducing the large network computational burden. Demand level as well as network size affects the relative performance of the local and iterative approaches. As demand level becomes higher, (1) in the small network, the local search tends to outperform the iterative search and (2) in the large network, vice versa.